Public Member Functions | Public Attributes | List of all members
dai::RawFeatureTrackerConfig::FeatureMaintainer Struct Reference

#include <RawFeatureTrackerConfig.hpp>

Public Member Functions

 DEPTHAI_SERIALIZE (FeatureMaintainer, enable, minimumDistanceBetweenFeatures, lostFeatureErrorThreshold, trackedFeatureThreshold)
 

Public Attributes

bool enable = true
 
float lostFeatureErrorThreshold = 50000
 
float minimumDistanceBetweenFeatures = 50
 
float trackedFeatureThreshold = 200000
 

Detailed Description

FeatureMaintainer configuration structure.

Definition at line 199 of file RawFeatureTrackerConfig.hpp.

Member Function Documentation

◆ DEPTHAI_SERIALIZE()

dai::RawFeatureTrackerConfig::FeatureMaintainer::DEPTHAI_SERIALIZE ( FeatureMaintainer  ,
enable  ,
minimumDistanceBetweenFeatures  ,
lostFeatureErrorThreshold  ,
trackedFeatureThreshold   
)

Member Data Documentation

◆ enable

bool dai::RawFeatureTrackerConfig::FeatureMaintainer::enable = true

Enable feature maintaining or not.

Definition at line 203 of file RawFeatureTrackerConfig.hpp.

◆ lostFeatureErrorThreshold

float dai::RawFeatureTrackerConfig::FeatureMaintainer::lostFeatureErrorThreshold = 50000

Optical flow measures the tracking error for every feature. If the point can’t be tracked or it’s out of the image it will set this error to a maximum value. This threshold defines the level where the tracking accuracy is considered too bad to keep the point.

Definition at line 217 of file RawFeatureTrackerConfig.hpp.

◆ minimumDistanceBetweenFeatures

float dai::RawFeatureTrackerConfig::FeatureMaintainer::minimumDistanceBetweenFeatures = 50

Used to filter out detected feature points that are too close. Requires sorting enabled in detector. Unit of measurement is squared euclidean distance in pixels.

Definition at line 210 of file RawFeatureTrackerConfig.hpp.

◆ trackedFeatureThreshold

float dai::RawFeatureTrackerConfig::FeatureMaintainer::trackedFeatureThreshold = 200000

Once a feature was detected and we started tracking it, we need to update its Harris score on each image. This is needed because a feature point can disappear, or it can become too weak to be tracked. This threshold defines the point where such a feature must be dropped. As the goal of the algorithm is to provide longer tracks, we try to add strong points and track them until they are absolutely untrackable. This is why, this value is usually smaller than the detection threshold.

Definition at line 226 of file RawFeatureTrackerConfig.hpp.


The documentation for this struct was generated from the following file:


depthai
Author(s): Martin Peterlin
autogenerated on Sat Mar 22 2025 02:58:20